System And Method For Capturing And Sharing A Location Based Experience

ABSTRACT

A system and method for capturing a location based experience at an event including a plurality of mobile devices having a camera employed near a point of interest to capture random, crowdsourced images and associated metadata near said point of interest. In a preferred form, the images include depth camera information from prepositioned devices around the point of interest during the event. A network communicates images, depth information, and metadata to build a 3D model of the region, preferably with the location of contributors known. Users connect to this experience platform to view the 3D model from a user selected location and orientation and to participate in experiences with, for example, a social network.

PRIORITY

The present application is a continuation from U.S. Ser. No. 13/774,710filed Feb. 22, 2013 which claims priority to U.S. 61/602,390 filed Feb.23, 2012.

BACKGROUND 1. Field of the Invention

The present invention relates to systems and methods for creating indoorand outdoor environments that include virtual models and images, andmethods and systems for using such created environments. In preferredforms, the environments are created in part using crowd sourced imagesand metadata and the environments are applied to social mediaapplications.

2. Description of the Related Art

Microsoft, Google, and Nokia (Navteq) have employed moving streetvehicles through most major cities in the world to capture images of thebuildings and environment as the vehicle traverses the street. In somecases, laser radar imagery (e.g. Light Detection and Ranging or “LIDAR”)also captures ranging data from the vehicle to capture data related tobuilding and street positions and structure, such as a building height.The images captured by the moving vehicle comprise photographs and videoimages that users can access from a mapping service (along withsatellite images in many cases). For example, Street View from Google isaccessed from Google Maps and Google Earth and provides panorama imagestaken from the acquisition vehicle as it moves along major streets. BingMaps from Microsoft is similar, see, e.g., U.S. Publication No.2011/0173565 and WO 2012/002811. Earthmine is similar but uses the Marscollection system. Nokia has its own version called “Journey View” whichoperates similarly. Such imagery are very useful, but acquisition islimited to dedicated vehicles traveling along major arteries. Otherapproaches use optical and LIDAR data captured from an aircraft.

Photo sharing sites have arisen where web based photo repositories(Photobucket) share photos of an event with authorized users. Examplesinclude Flickr, Photobucket, Picasa, Shutterfly, Beamr and Snapfish.Further, social networks such as Facebook and Google+ allow groups topost photos of an event and share photographs with friends. Such photorepositories and social networks are useful in sharing an event withfriends, but are limited in realism and interaction. Further, manysocial networks operate as photo repositories and traditional photorepositories have become social networks—blurring the distinctionbetween them. Further, photo improvement sites have become common. Forexample, Instagram, Camera+, and Pinterest.

There is a need for an accurate method and system to create anenvironment and to update an environment so that it is accurate, featurerich, and current. For example, U.S. Publication No. 2011/0313779illustrates one approach to update points of interest by collecting userfeedback. Additionally, many environments are simply not available, suchas parks, indoor locations and any locations beyond major streets inmajor cities. Further, it would be an advance to be able to sharelocation based experiences beyond just photos of an event posted afterthe event.

Related patents and applications describe various improvements onlocation based experiences, for example: U.S. Pat. Nos. 7,855,638 and7,518,501 and U.S. Publication Nos. 2011/0282799, 2007/0018880,2012/0007885, and 2008/0259096 (sometimes referred to herein as “RelatedPatents”). All references cited herein are incorporated by reference tothe maximum extent allowable by law, but such incorporation should notbe construed as an admission that a reference is prior art.

SUMMARY

The problems outlined above are addressed by the systems and methods forcreating and sharing an environment and an experience in accordance withthe present invention. Broadly speaking, a system for creating anenvironment and for sharing an experience includes a plurality of mobiledevices having a camera employed near a point of interest to capturerandom images and associated metadata near said point of interest,wherein the metadata for each image includes location of the mobiledevice and the orientation of the camera. A wireless networkcommunicates with the mobile devices to accept the images and metadata.An image processing server is connected to the network for receiving theimages and metadata, with the server processing the images to determinethe location of various targets in the images and to build a 3D model ofthe region near the point of interest. Preferably, an experienceplatform connected to the image processing server for storing the 3Dmodel. A plurality of users connect to the experience platform to viewthe point of interest from a user selected location and orientation.

In a preferred form, the experience platform includes a plurality ofimages associated with locations near the point of interest. In anotherform the users connected to the experience platform can view imagesassociated with a user selected location and orientation. In anotherform, the processing server stitches a number of images together to forma panorama. Preferably, the users connected to the experience platformcan view panoramas associated with a user selected location andorientation.

Broadly speaking, a system for creating an environment for use with alocation based experience includes a plurality of mobile devicesaccompanying a number of random contributors, each having a camera tocapture random images and associated metadata near a point of interest,wherein the metadata for each image includes location of the mobiledevice and the orientation of the camera. The system includes a wirelessnetwork communicating with the mobile devices to accept the images andmetadata. An image processing server is connected to the network forreceiving the images and metadata, wherein the server processes theimages to determine the location of various targets in the images and tobuild a 3D model of the region near the point of interest. Preferablythe server processes the images to create panoramas associated with anumber of locations near the point of interest.

In one form the present invention includes a method of sharing contentin a location based experience, where a plurality of images andassociated metadata are captured. The images and metadata are processedto build a 3D model of the region near a point of interest. The methodincludes storing the images and 3D model in an experience platformconnected to a network. The experience platform is accessed using thenetwork to access the 3D model and images. A user selects a location andorientation in the 3D model and views the point of interest from theselected location and orientation.

In another form, sharing an experience or viewing an event involvesadding or changing an advertisement based on context, such as marketingfactors. In another form, a product image may be inserted into the view.In other cases, the context of the advertisement or product placementmight be determined by the personal information of the individualspectator as gleaned from the spectator's viewing device, social mediaor cloud based data. In other forms, an advertisement might be added orchanged based on the social network tied to an event or experience orthe nature of the event.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1a is a perspective view of a Plaza used as an example herein, andFIG. 1b is a plan view of the Plaza of FIG. 1 a;

FIG. 2 is a front elevational view of a mobile device in a preferredembodiment;

FIG. 3 is a functional diagram of a network system in accordance withthe present invention;

FIG. 4 is a front elevational view of the mobile device of FIG. 2depicting functional objects;

FIG. 5 is a back elevational view of the device of FIGS. 2 and 4;

FIG. 6 is a functional hardware diagram of the device of FIGS. 2, 4, and5;

FIG. 7 is a front elevational view of the device of FIG. 2 showing afirst example;

FIG. 8 is a front elevational view of the device of FIG. 2 showing asecond example;

FIG. 9 is a front elevational view of the device of FIG. 2 showing athird example;

FIG. 10 is a perspective view of another mobile device of the presentinvention;

FIG. 11A is a perspective, aerial view of a portion of a city where alow resolution wire frame is depicted;

FIG. 11B is a perspective, aerial view of the same portion of a citywhere a refined resolution is depicted;

FIG. 11C is a perspective, aerial view of the same portion of a citywhere a detailed resolution is depicted;

FIG. 11D is a perspective, aerial view of the same portion of a citywhere a fine, photorealistic resolution is depicted;

FIG. 12 is a table of EXIF metadata for an acquired image;

FIGS. 13a and 13b are diagrams showing Photogrammetry basic theory;

FIG. 14 is a schematic depicting image alignment and registration;

FIG. 15 is a schematic depicting three different views of a target;

FIG. 16A illustrates a conventional camera;

FIG. 16B illustrates the geometry of a plenoptic camera;

FIG. 17 is a perspective view of a room having an embodiment of animmersive environment; and

FIG. 18 is a perspective view of another room, specifically a weddingchapel, illustrating another environment.

DESCRIPTION OF PREFERRED EMBODIMENTS I. Overview

In an exemplary form, a 3D model or “virtual model” is used as astarting point, such as the image of the plaza of FIG. 1 a. Multipleusers (or a single user taking multiple pictures) take pictures (images)of the plaza from various locations, marked A-E in FIG. 1b using amobile device, such as smart phone 10 shown in FIG. 3. Each image A-Eincludes not only the image, but metadata associated with the imageincluding EXIF data, time, position, and orientation. In this example,the images and metadata are uploaded as they are acquired to acommunication network 205 (e.g., cell network) connected to an imageprocessing server 211 (FIG. 3). In some embodiments, the mobile devicealso includes one or more depth cameras as shown in FIG. 2.

The image processing server 211 uses the network 205 and GPS informationfrom the phone 10 to process the metadata to obtain very accuratelocations for the point of origin of images A-E. Using image matchingand registration techniques the images are stitched together to formmosaics and panoramas, and to refine a 3D model of the plaza. Inrefining the 3D model of the plaza, image recognition techniques mayremove people from the images to focus on building a very accurate 3Dmodel of the plaza without clutter and privacy issues. The resulting“environment” is an accurate 3D model of the plaza that can be recreatedand viewed from any location in the plaza and user selected orientationfrom the user-chosen location. Further, many locations in the plaza haveimages, mosaics or panoramas of stitched images associated with thelocation or can be created from images associated with nearby locations.

In one example, a user remote from the plaza at the time of an event canparticipate in the event by accessing the experience platform 207 andviewing the plaza in essentially real time. All or selected participantsin the event can be retained in the images, and even avatars employed torepresent participants at the event. The remote user, therefore canobserve the plaza during the event selecting a virtual view of the plazaor photographic view of the plaza during the event.

In another example, the plaza described above for an event becomesnewsworthy for the event. Remote users or a news organization can replaythe event using the historical images for the event accessed from theexperience platform.

In still another example, a user physically attending the event at theplaza can participate by accessing the experience platform 207 andidentifying participants in the event using augmented reality and/orobject related content.

II. Explanation of Terms

As used herein, the term “image” refers to one or a series of imagestaken by a camera (e.g., a still camera, digital camera, video camera,camera phone, etc.) or any other imaging equipment. The image isassociated with metadata, such as EXIF, time, location, tilt angle, andorientation of the imaging device (e.g., camera) at the time of imagecapture. Depth camera information and audio can also be considered animage or part of an image.

As used herein, the term “point of interest” refers to any point inspace specified by a user in an image. By way of example, the point ofinterest in an image can be an observation deck or a roof of a tower, anantenna or a window of a building, a carousel in a park, etc. “Points ofinterest” are not limited to only stationary objects but can includemoving objects as well.

The most common positioning technology is GPS. As used herein,GPS—sometimes known as GNSS—is meant to include all of the current andfuture positioning systems that include satellites, such as the U.S.Navistar, GLONASS, Galileo, EGNOS, WAAS, MSAS, BeiDou NavigationSatellite System (China), QZSS, etc. The accuracy of the positions,particularly of the participants, can be improved using knowntechniques, often called differential techniques, such as WAAS (widearea), LAAS (local area), Carrier-Phase Enhancement (CPGPS), Space BasedAugmentation Systems (SBAS); Wide Area GPS Enhancement (WAGE), orRelative Kinematic Positioning (RKP). Even without differentialcorrection, numerous improvements are increasing GPS accuracy, such asthe increase in the satellite constellation, multiple frequencies (L₁,L₂, L₅), modeling and AGPS improvements, software receivers, and groundstation improvements. Of course, the positional degree of accuracy isdriven by the requirements of the application. In the golf example usedto illustrate a preferred embodiment, sub five meter accuracy providedby WAAS with Assisted GPS would normally be acceptable. In building amodel in accordance with the present invention, AGPS, WAAS, and postprocessing using time and differential correction can result in submeterposition accuracy. Further, some “experiences” might be held indoors andthe same message enhancement techniques described herein used. Suchindoor positioning systems include AGPS, IMEO, Wi-Fi (Skyhook),WIFISLAM, Cell ID, pseudolites, repeaters, RSS on any electromagneticsignal (e.g. TV) and others known or developed.

The term “geo-referenced” means a message fixed to a particular locationor object. Thus, the message might be fixed to a venue location, e.g.,golf course fence or fixed to a moving participant, e.g., a moving golfcar or player. An object is typically geo-referenced using either apositioning technology, such as GPS, but can also be geo-referencedusing machine vision. If machine vision is used (i.e. objectrecognition), applications can be “markerless” or use “markers,”sometimes known as “fiducials.” Marker-based augmented reality oftenuses a square marker with a high contrast. In this case, four cornerpoints of a square are detected by machine vision using the squaremarker and three-dimensional camera information is computed using thisinformation. Other detectable sources have also been used, such asembedded LED's or special coatings or QR codes. Applying AR to a markerwhich is easily detected is advantageous in that recognition andtracking are relatively accurate, even if performed in real time. So, inapplications where precise registration of the AR message in thebackground environment is important, a marker based system has someadvantages.

In a “markerless” system, AR uses a general natural image instead of afiducial. In general, markerless AR uses a feature point matchingmethod. Feature point matching refers to an operation for searching forand connecting the same feature points in two different images. Onemethod for feature recognition is discussed herein in connection withPhotsyth. A method for extracting a plane uses Simultaneous Localizationand Map-building (SLAM)/Parallel Tracking And Mapping (PTAM) algorithmfor tracking three-dimensional positional information of a camera andthree-dimensional positional information of feature points in real timeand providing AR using the plane has been suggested. However, since theSLAM/PTAM algorithm acquires the image to search for the feature points,computes the three-dimensional position of the camera and thethree-dimensional positions of the feature points, and provides AR basedon such information, a considerable computation is necessary. A hybridsystem can also be used where a readily recognized symbol or brand isgeo-referenced and machine vision substitutes the AR message.

In the present application, the term “social network” is used to referto any process or system that tracks and enables connections betweenmembers (including people, businesses, and other entities) or subsets ofmembers. The connections and membership may be static or dynamic and themembership can include various subsets within a social network. Forexample, a person's social network might include a subset of membersinterested in art and the person shares an outing to a sculpture gardenonly with the art interest subset. Further, a social network might bedynamically configured. For example, a social network could be formedfor “Nasher Sculpture Garden” for September 22 and anyone interestedcould join the Nasher Sculpture Garden September 22 social network.Alternatively, anyone within a certain range of the event might bepermitted to join. The permutations involving membership in a socialnetwork are many and not intended to be limiting.

A social network that tracks and enables the interactive web by engagingusers to participate in, comment on and create content as a means ofcommunicating with their social graph, other users and the public. Inthe context of the present invention, such sharing and social networkparticipation includes participant created content and spectator createdcontent and of course, jointly created content. For example, the createdcontent can be interactive to allow spectators to add content to theparticipant created event. The distinction between photo repositories,such as FLIKR and Photobucket and social networks has become blurred,and the two terms are sometimes used interchangeably herein.

Examples of conventional social networks include LinkedIn.com orFacebook.com, Google Plus, Twitter (including Tweetdeck), socialbrowsers such as Rockmelt, and various social utilities to supportsocial interactions including integrations with HTML5 browsers. Thewebsite located atwww.Wikipedia.org/wiki/list_of_social_networking_sites lists severalhundred social networks in current use. Dating sites, Listservs, andInterest groups can also serve as a social network. Interest groups orsubsets of a social network are particularly useful for inviting membersto attend an event, such as Google+ “circles” or Facebook “groups.”Individuals can build private social networks. Conventional socialnetworking websites allow members to communicate more efficientlyinformation that is relevant to their friends or other connections inthe social network. Social networks typically incorporate a system formaintaining connections among members in the social network and links tocontent that is likely to be relevant to the members. Social networksalso collect and maintain information or it may be dynamic, such astracking a member's actions within the social network. The methods andsystem hereof relate to dynamic events of a member's actions sharedwithin a social network about the members of the social network. Thisinformation may be static, such as geographic location, employer, jobtype, age, music preferences, interests, and a variety of otherattributes,

In the present application, the venue for an event or “experience” canbe a real view or depicted as a photo background environment or avirtual environment, or a mixture, sometimes referred to as “mixedreality.” A convenient way of understanding the environment of thepresent invention is as a layer of artificial reality or “augmentedreality” images overlaid the event venue background. There are differentmethods of creating the event venue background as understood by one ofordinary skill in the art. For example, an artificial backgroundenvironment can be created by a number of rendering engines, sometimesknown as a “virtual” environment. See, e.g., Nokia's (through its Navteqsubsidiary) Journey View which blends digital images of a realenvironment with an artificial 3D rendering. A “virtual” environment or3D model can be at different levels of resolutions, such as that shownin Figs. A-11D. A real environment can be the background as seen throughglasses of FIG. 10, but can also be created using a digital image,panorama or 3D model. Such a digital image can be stored and retrievedfor use, such as a “street view” or photo, video, or panorama, or othertype of stored image. Alternatively, many mobile devices have a camerafor capturing a digital image which can be used as the backgroundenvironment. Such a camera-sourced digital image may come from the user,friends, social network groups, crowd-sourced, or service provided.Because the use of a real environment as the background is common,“augmented reality” often refers to a technology of inserting a virtualreality graphic (object) into an actual digital image and generating animage in which a real object and a virtual object are mixed (i.e. “mixedreality”). Augmented reality is often characterized in thatsupplementary information using a virtual graphic may be layered orprovided onto an image acquired of the real world. Multiple layers ofreal and virtual reality can be mixed. In such applications theplacement of an object or “registration” with other layers is important.That is, the position of objects or layers relative to each other basedon a positioning system should be close enough to support theapplication. As used herein, “artificial reality” (“AR”) is sometimesused interchangeably with “virtual,” “mixed,” or “augmented” reality, itbeing understood that the background environment can be real or virtual.

The present application uses the terms “platform” and “server”interchangeably and describes various functions associated with such aserver, including data and applications residing on the server. Suchfunctional descriptions does not imply that all functions could notreside on the same server or multiple servers or remote and distributedservers, or even functions shared between clients and servers as readilyunderstood in the art.

The present application uses the term “random” when discussing an imageto infer that the acquisition of multiple images is not coordinated,i.e. target, orientation, time, etc. One category of acquired randomimages is from “crowdsourcing.”

III. Mobile Device

In more detail, FIG. 4 is a front elevational view of a mobile device10, such as a smart phone, which is the preferred form factor for thedevice 10 discussed herein to illustrate certain aspects of the presentinvention. Mobile device 10 can be, for example, a handheld computer, atablet computer, a personal digital assistant, goggles or glasses,contact lens, a cellular telephone, a wrist-mounted computer, a camerahaving a GPS and a radio, a GPS with a radio, a network appliance, acamera, a smart phone, an enhanced general packet radio service (EGPRS)mobile phone, a network base station, a media player, a navigationdevice, an email device, a game console, or other electronic device or acombination of any two or more of these data processing devices or otherdata processing.

Mobile device 10 includes a touch-sensitive graphics display 102. Thetouch-sensitive display 102 can implement liquid crystal display (LCD)technology, light emitting polymer display (LPD) technology, or someother display technology. The touch-sensitive display 102 can besensitive to haptic and/or tactile contact with a user.

The touch-sensitive graphics display 102 can comprise amulti-touch-sensitive display. A multi-touch-sensitive display 102 can,for example, process multiple simultaneous touch points, includingprocessing data related to the pressure, degree and/or position of eachtouch point. Such processing facilitates gestures and interactions withmultiple fingers, chording, and other interactions. Othertouch-sensitive display technologies can also be used, e.g., a displayin which contact is made using a stylus or other pointing device. Anexample of a multi-touch-sensitive display technology is described inU.S. Pat. Nos. 6,323,846; 6,570,557; 6,677,932; and U.S. Publication No.2002/0015024, each of which is incorporated by reference herein in itsentirety. Touch screen 102 and touch screen controller can, for example,detect contact and movement or break thereof using any of a plurality oftouch sensitivity technologies, including but not limited to capacitive,resistive, infrared, and surface acoustic wave technologies, as well asother proximity sensor arrays or other elements for determining one ormore points of contact with touch screen 102.

Mobile device 10 can display one or more graphical user interfaces onthe touch-sensitive display 102 for providing the user access to varioussystem objects and for conveying information to the user. The graphicaluser interface can include one or more display objects 104, 106, 108,110. Each of the display objects 104, 106, 108, 110 can be a graphicrepresentation of a system object. Some examples of system objectsinclude device functions, applications, windows, files, alerts, events,or other identifiable system objects.

Mobile device 10 can implement multiple device functionalities, such asa telephony device, as indicated by a phone object; an e-mail device, asindicated by the e-mail object; a network data communication device, asindicated by the Web object; a Wi-Fi base station device (not shown);and a media processing device, as indicated by the media player object.For convenience, the device objects, e.g., the phone object, the e-mailobject, the Web object, and the media player object, can be displayed inmenu bar 118.

Each of the device functionalities can be accessed from a top-levelgraphical user interface, such as the graphical user interfaceillustrated in FIG. 4. Touching one of the objects e.g. 104, 106, 108,110 etc. can, for example, invoke the corresponding functionality. Inthe illustrated embodiment, object 106 represents an Artificial Realityapplication in accordance with the present invention. Object 110 enablesthe functionality of one or more depth cameras.

Upon invocation of particular device functionality, the graphical userinterface of mobile device 10 changes, or is augmented or replaced withanother user interface or user interface elements, to facilitate useraccess to particular functions associated with the corresponding devicefunctionality. For example, in response to a user touching the phoneobject, the graphical user interface of the touch-sensitive display 102may present display objects related to various phone functions;likewise, touching of the email object may cause the graphical userinterface to present display objects related to various e-mailfunctions; touching the Web object may cause the graphical userinterface to present display objects related to various Web-surfingfunctions; and touching the media player object may cause the graphicaluser interface to present display objects related to various mediaprocessing functions.

The top-level graphical user interface environment or state of FIG. 4can be restored by pressing button 120 located near the bottom of mobiledevice 10. Each corresponding device functionality may havecorresponding “home” display objects displayed on the touch-sensitivedisplay 102, and the graphical user interface environment of FIG. 4 canbe restored by pressing the “home” display object or reset button 120.

The top-level graphical user interface is shown in FIG. 1 and caninclude additional display objects, such as a short messaging service(SMS) object, a calendar object, a photos object, a camera object 108, acalculator object, a stocks object, a weather object, a maps object, anotes object, a clock object, an address book object, and a settingsobject, as well as AR object 106 and depth camera object 110. Touchingthe SMS display object can, for example, invoke an SMS messagingenvironment and supporting functionality. Likewise, each selection of adisplay object can invoke a corresponding object environment andfunctionality.

Mobile device 10 can include one or more input/output (I/O) devicesand/or sensor devices. For example, speaker 122 and microphone 124 canbe included to facilitate voice-enabled functionalities, such as phoneand voice mail functions. In some implementations, loud speaker 122 canbe included to facilitate hands-free voice functionalities, such asspeaker phone functions. An audio jack can also be included for use ofheadphones and/or a microphone.

A proximity sensor (not shown) can be included to facilitate thedetection of the user positioning mobile device 10 proximate to theuser's ear and, in response, disengage the touch-sensitive display 102to prevent accidental function invocations. In some implementations, thetouch-sensitive display 102 can be turned off to conserve additionalpower when mobile device 10 is proximate to the user's ear.

Other sensors can also be used. For example, an ambient light sensor(not shown) can be utilized to facilitate adjusting the brightness ofthe touch-sensitive display 102. An accelerometer (FIG. 6) can beutilized to detect movement of mobile device 10, as indicated by thedirectional arrow. Accordingly, display objects and/or media can bepresented according to a detected orientation, e.g., portrait orlandscape.

Mobile device 10 may include circuitry and sensors for supporting alocation determining capability, such as that provided by the globalpositioning system (GPS) or other positioning system (e.g., Cell ID,systems using Wi-Fi access points, television signals, cellular grids,Uniform Resource Locators (URLs)). A positioning system (e.g., a GPSreceiver, FIG. 6) can be integrated into the mobile device 10 orprovided as a separate device that can be coupled to the mobile device10 through an interface (e.g., port device 132) to provide access tolocation-based services.

Mobile device 10 can also include one or more front camera lens andsensor 140 and depth camera 142. In a preferred implementation, abackside camera lens and sensor 141 is located on the back surface ofthe mobile device 10 as shown in FIG. 5. The conventional RGB cameras140, 141 can capture still images and/or video. The camera subsystemsand optical sensors 140, 141 may comprise, e.g., a charged coupleddevice (CCD) or a complementary metal-oxide semiconductor (CMOS) opticalsensor, can be utilized to facilitate camera functions, such asrecording photographs and video clips. Camera controls (zoom, pan,capture and store) can be incorporated into buttons 134-136 (FIG. 4.) Insome embodiments, the cameras can be of different types. For example,cameras 140, 141 might be a conventional RGB camera, while cameras 142,143 comprise a range camera, such as a plenoptic camera. Similarly,other sensors can be incorporated into device 10. For example, sensors146, 148 might be other types of range cameras, such as a time of flightcamera (TOF) or LIDAR with 146 the illuminator and 148 the imager.Alternatively, in several embodiments the sensors are part of astructured light system where sensor 146 is an IR emitter and sensor 148is an IR receptor that functions as a depth camera, such as Capri 1.25available from Primesense.

The preferred mobile device 10 includes a GPS positioning system. Inthis configuration, another positioning system can be provided by aseparate device coupled to the mobile device 10, or can be providedinternal to the mobile device. Such a positioning system can employpositioning technology including a GPS, a cellular grid, URL's, IMEO,pseudolites, repeaters, Wi-Fi or any other technology for determiningthe geographic location of a device. The positioning system can employ aservice provided by a positioning service such as, for example, a Wi-FiRSS system from SkyHook Wireless of Boston, Mass., or Rosum Corporationof Mountain View, Calif. In other implementations, the positioningsystem can be provided by an accelerometer and a compass using deadreckoning techniques starting from a known (e.g. determined by GPS)location. In such implementations, the user can occasionally reset thepositioning system by marking the mobile device's presence at a knownlocation (e.g., a landmark or intersection). In still otherimplementations, the user can enter a set of position coordinates (e.g.,latitude, longitude) for the mobile device. For example, the positioncoordinates can be typed into the phone (e.g., using a virtual keyboard)or selected by touching a point on a map. Position coordinates can alsobe acquired from another device (e.g., a car navigation system) bysyncing or linking with the other device. In other implementations, thepositioning system can be provided by using wireless signal strength andone or more locations of known wireless signal sources (Wi-Fi, TV, FM)to provide the current location. Wireless signal sources can includeaccess points and/or cellular towers. Other techniques to determine acurrent location of the mobile device 10 can be used and otherconfigurations of the positioning system are possible.

Mobile device 10 can also include one or more wireless communicationsubsystems, such as a 802.11b/g/n communication device, and/or aBluetooth™ communication device, in addition to near fieldcommunications. Other communication protocols can also be supported,including other 802.x communication protocols (e.g., WiMax, Wi-Fi), codedivision multiple access (CDMA), global system for mobile communications(GSM), Enhanced Data GSM Environment (EDGE), 3G (e.g., EV-DO, UMTS,HSDPA), etc. Additional sensors are incorporated into the device 10,such as accelerometer, digital compass and gyroscope, see FIG. 6. Apreferred device would include a rangefinder as well. Further,peripheral sensors, devices and subsystems can be coupled to peripheralsinterface 132 to facilitate multiple functionalities. For example, amotion sensor, a light sensor, and/or a proximity sensor can be coupledto peripherals interface 132 to facilitate the orientation, lighting andproximity functions described with respect to FIGS. 4 and 6. Othersensors can also be connected to peripherals interface 132, such as aGPS receiver, a temperature sensor, a biometric sensor, RFID, or anyDepth camera or other sensing device, to facilitate relatedfunctionalities. Preferably, the present invention makes use of as manysensors as possible to collect metadata associated with an image. Thequantity and quality of metadata aids not only yields better results,but reduces image processing time.

Port device 132, is e.g., a Universal Serial Bus (USB) port, or adocking port, or some other wired port connection. Port device 132 can,for example, be utilized to establish a wired connection to othercomputing devices, such as other communication devices 10, a personalcomputer, a printer, or other processing devices capable of receivingand/or transmitting data. In some implementations, port device 132allows mobile device 10 to synchronize with a host device using one ormore protocols.

Input/output and operational buttons are shown at 134-136 to control theoperation of device 10 in addition to, or in lieu of the touch sensitivescreen 102. Mobile device 10 can include a memory interface to one ormore data processors, image processors and/or central processing units,and a peripherals interface (FIG. 6). The memory interface, the one ormore processors and/or the peripherals interface can be separatecomponents or can be integrated in one or more integrated circuits. Thevarious components in mobile device 10 can be coupled by one or morecommunication buses or signal lines.

Preferably, the mobile device includes a graphics processing unit (GPU)coupled to the CPU (FIG. 6). While a Nvidia GeForce GPU is preferred, inpart because of the availability of CUDA, any GPU compatible with OpenGLis acceptable. Tools available from Kronos allow for rapid developmentof 3D models. Of course, a high performance System on a Chip (SOC) is apreferred choice if cost permits, such as an NVIDIA Tegra 4i with 4 CPUcores, 60 GPU cores, and an LTE modem.

The I/O subsystem can include a touch screen controller and/or otherinput controller(s). The touch-screen controller can be coupled to touchscreen 102. The other input controller(s) can be coupled to otherinput/control devices 132-136, such as one or more buttons, rockerswitches, thumb-wheel, infrared port, USB port, and/or a pointer devicesuch as a stylus. The one or more buttons (132-136) can include anup/down button for volume control of speaker 122 and/or microphone 124,or to control operation of cameras 140,141. Further, the buttons(132-136) can be used to “capture” and share an image of the event alongwith the location of the image capture. Finally, “softkeys” can be usedto control a function—such as controls appearing on display 102 forcontrolling a particular application (AR application 106 for example).

In one implementation, a pressing of button 136 for a first duration maydisengage a lock of touch screen 102; and a pressing of the button for asecond duration that is longer than the first duration may turn thepower on or off to mobile device 10. The user may be able to customize afunctionality of one or more of the buttons. Touch screen 102 can, forexample, also be used to implement virtual or soft buttons and/or akeyboard.

In some implementations, mobile device 10 can present recorded audioand/or video files, such as MP3, AAC, and MPEG files. In someimplementations, mobile device 10 can include the functionality of anMP3 player, such as an iPod™. Mobile device 10 may, therefore, include a36-pin connector that is compatible with the iPod. Other input/outputand control devices can also be used.

The memory interface can be coupled to a memory. The memory can includehigh-speed random access memory and/or non-volatile memory, such as oneor more magnetic disk storage devices, one or more optical storagedevices, and/or flash memory (e.g., NAND, NOR). The memory can store anoperating system, such as Darwin, RTXC, LINUX, UNIX, OS X, WINDOWS, oran embedded operating system such as VxWorks. The operating system mayinclude instructions for handling basic system services and forperforming hardware dependent tasks. In some implementations, theoperating system handles timekeeping tasks, including maintaining thedate and time (e.g., a clock) on the mobile device 10. In someimplementations, the operating system can be a kernel (e.g., UNIXkernel).

The memory may also store communication instructions to facilitatecommunicating with one or more additional devices, one or more computersand/or one or more servers. The memory may include graphical userinterface instructions to facilitate graphic user interface processing;sensor processing instructions to facilitate sensor-related processingand functions; phone instructions to facilitate phone-related processesand functions; electronic messaging instructions to facilitateelectronic-messaging related processes and functions; web browsinginstructions to facilitate web browsing-related processes and functions;media processing instructions to facilitate media processing-relatedprocesses and functions; GPS/Navigation instructions to facilitate GPSand navigation-related processes and instructions; camera instructionsto facilitate camera-related processes and functions; other softwareinstructions to facilitate other related processes and functions; and/ordiagnostic instructions to facilitate diagnostic processes andfunctions. The memory can also store data, including but not limited tocoarse information, locations (points of interest), personal profile,documents, images, video files, audio files, and other data. Theinformation can be stored and accessed using known methods, such as astructured or relative database.

Portable device 220 of FIG. 10 is an alternative embodiment in theconfiguration of glasses or goggles and includes a GPS and patch antenna232, microprocessor and GPU 234, camera 222, and radio 236. Controls,such as the directional pad 224, are on the side frames (opposite sidenot shown). In addition to or in lieu of the control pad 224, amicrophone and voice commands run by processor 234, or gestural commandscan be used. Batteries are stored in compartment 242. The displays aretransparent LCD's as at 244. Sensors 246, 248 are preferably associatedwith a depth camera, such as a TOF camera, structured light camera, orLIDAR, as described herein. Alternatively both sensors might comprise aplenoptic camera. Examples of similar devices are the MyVue headset madeby MicroOptical Corp. of Westwood, Mass. (see, e.g., U.S. Pat. No.6,879,443), Vuzix Wrap 920 AR, 1200 VR, Smart Glasses M 100 and Tac-EyeLT available from Vuzix Corporation, Rochester, N.Y. A more immersiveexperience is available using the Occulus Rift head mounted display(HMD) available from Occulus VR of Southern California. Such immersivevirtual reality HMD's are advantageous in certain applications and theterms “glasses” or “goggles” when used in the present application aremeant to include such immersive HMD's.

A particular benefit of the use of wearable glasses such as theembodiment of FIG. 10 is the ability to incorporate augmented realitymessages and information, e.g. point of interest overlays onto the“real” background. Of course, augmented reality can also be used withportable device 10 of FIGS. 4-9 using one or more cameras, 140, 141,142, 143, 146 or 148. In the golf example, a golfer wearing glasses 220can see the AR messages and course information and selectively highlighta particular message and additional information relative to that message(e.g. layup area, wind used in club selection, next best club selection,status of other golfers rounds, etc.). See, e.g. U.S. Pat. Nos.7,002,551; 6,919,867; 7,046,214; 6,945,869; 6,903,752; 6,317,127 (hereinincorporated by reference).

Another benefit of wearable glasses such as the embodiment of FIG. 10 isthe ability to easily control the glasses 220 or any tethered smartphoneby use of a gestural interface. That is, in addition to or as analternative to buttons or keys on glasses 220 or the use of voicecommands, gestures can be used to control operation of glasses 220. Suchgestures can be recognized by any of the cameras or sensors, dependingon the application. Depth cameras (such as Kinect or Claris) have provenparticularly adapted for use in a gestural interface. However,conventional cameras such as RGB camera 222 have also been employed forsimple gesture recognition. (See, Flutter of Mountain View, Calif.). Seealso, U.S. Publication Nos. 2010/0083190; 2002/0118880; 2010/0153457;2010/0199232; and U.S. Pat. No. 7,095,401.

There are several different types of “range” or “depth” cameras that canbe used in a mobile device, such as mobile devices 10, 220. Broadlyspeaking, depth cameras use:

-   -   Stereo triangulation    -   Sheet of light triangulation    -   Structured light    -   Time-of-flight    -   Interferometry    -   Coded Aperture        In the present application, “depth camera” or alternatively        “range camera” is sometimes used to refer to any of these types        of cameras.

While certain embodiments of the present invention can use differenttypes of depth cameras, the use of triangulation (stereo), structuredlight, and time of flight (TOF) cameras are advantageous in certainembodiments discussed herein. As shown in FIG. 15, with a conventionalcamera, photographers at points A, B, and C are photographing a Target200. The metadata (EXIF, FIG. 12) gives orientation and Depth of Fieldfrom each point A, B, and C. I.e. the orientations and depth of fieldassociated with vectors from the points A, B, and C to the target inFIG. 1 b. Depth of field refers to the range of distance that appearsacceptably sharp, i.e. in focus. It varies depending on camera type,aperture and focusing distance, among other things. This “sharpness” or“focus” is a range, and often referred to as a circle of confusion. Anacceptably sharp circle of confusion is loosely defined as one whichwould go unnoticed when enlarged to a standard 8×10 inch print, andobserved from a standard viewing distance of about 1 foot. For digitalimaging, an image is considered in focus if this blur radius is smallerthan the pixel size p.

As shown in FIG. 15, the metadata greatly aids in locating the positionof the target 200, and in this example, location data of Points A, B andC are known from GPS data. However, the location of the target convergesto a smaller “area” as more points and images are taken of the target200. In FIG. 15 an image is acquired from Point A along vector 210 totarget 200. The area of uncertainty is denoted as arc 216. As can beseen, with images taken from Points B, C along vectors 212, 214, thelocation of the target converges to a small area denoted at 200.

In stereo triangulation, the present application contemplates thatdifferent cameras are used from different locations A, B, C as shown inFIG. 15. Alternatively, a single camera with 2 sensors offset from eachother, such as the BumbleBee2 available from Point Grey Research Inc. ofRichmond, B.C., Canada can be used to obtain depth information from apoint to the target, e.g. Point A to target 200. See, U.S. Pat. Nos.6,915,008; 7,692,684; 7,167,576.

Structured Light as a depth imaging technology has gained popularitywith the introduction of the Microsoft Kinect game system (see also AsusXtionPro). A structured light imaging systems projects a known lightpattern into the 3D scene, viewed by camera(s). Distortion of theprojected light pattern allows computing the 3D structure imaged by theprojected light pattern. Generally, the imaging system projects a knownpattern (Speckles) in Near-Infrared light. A CMOS IR camera observes thescene. Calibration between the projector and camera has to be known.Projection generated by a diffuser and diffractive element of IR light.Depth is calculated by triangulation of each speckle between a virtualimage (pattern) and observed pattern. Of course, a number of varietiesof emittors and detectors are equally suitable, such as light patternsemitted by a MEMS laser or infrared light patterns projected by an LCD,LCOS, or DLP projector. Primesense manufactures the structured lightsystem for Kinect and explains in greater detail its operation in WO2007/043036 and U.S. Pat. Nos. 7,433,024; 8,050,461; 8,350,847. Seealso, U.S. Publication Nos. 2012/0140109; 2012/0042150; 2009/0096783;2011/0052006, 2011/0211754. See also, U.S. Publication Nos.2012/0056982; 2008/0079802; 2012/0307075; and U.S. Pat. Nos. 8,279,334;6,903,745; 8,044,996 (incorporated by reference). Scanners usingstructured light are available from Matterport of Mountain View, Calif.

The current Kinect system uses an infrared projector, an infrared camera(detector) and an RGB camera. The current Kinect system has a Depthresolution of 640×480 pixels, an RGB resolution: 1600×1200 pixels,images at 60 FPS, has an Operation range of 0.8 m˜3.5 m, spatial x/yresolution of 3 mm @2 m distance and depth z resolution of 1 cm @2 mdistance. The system allows for marker less human tracking, gesturerecognition, facial recognition, motion tracking. By extracting manyinterest points at local geodesic extrema with respect to the bodycentroid during the calibration stage, the system can train a classifieron depth image paths and classify anatomical landmarks (e.g. head,hands, feet) of several individuals.

New Kinect systems can obtain the same resolution at distanceapproaching 60 meters and accommodate more individuals and a greaternumber of anatomical landmarks. The new Kinect systems reportedly have afield of view of 70 degrees horizontally and 60 degrees vertically a920×1080 camera changing from 24-bit RGB color to 16-bit YUV. The videowill stream at 30 fps. The depth resolution also improves from a 320×240to 512×424, and it will employ an IR stream—unlike the current-genKinect—so the device can see better in an environment with limitedlight. Further, latency will be reduced by incorporating USB 3.0.Further, Primesense has recently introduced an inexpensive, smallversion of its sensor system that can be incorporated into mobiledevices, the embedded 3D sensor, Capri 1.25. For example, in FIG. 5,sensors 146, 148 in some applications constitute emitters/receptors fora structured light system.

A time of flight (TOF) camera is a class of LIDAR and includes at leastan illumination unit, lens and an image sensor. The illumination unittypically uses an IR emitter and the image sensor measures the time thelight travels from the illumination unit to the object and back. Thelens gathers and projects the reflected light onto the image sensor (aswell as filtering out unwanted spectrum or background light.) Forexample, in FIG. 5, in some embodiments sensor 146 comprises anillumination sensor and senor 148 is the image sensor. Alternatively,sensors 146, 148 can operate as a part of a scanned or scannerless LIDARsystem using coherent or incoherent light in other spectrums. Such TOFcameras are available from PMDVision (Camcube or Camboard), MesaImaging, Fotonic (C-40, C-70) or ifm. Image processing software isavailable from Metrilus, GmbH of Erlangen Germany.

Plenoptic Cameras can be used as any of the sensors 140-148 in FIG. 5 or222, 246, 248 in FIG. 10. Plenoptic Cameras sample the plenopticfunction and are also known as Light Field cameras and sometimesassociated with computational photography. Plenoptic cameras areavailable from several sources, such as Lytos, Adobe, Raytrix andPelican Imaging. See, e.g., U.S. Pat. Nos. 8,279,325; 8,289,440;8,305,456; 8,265,478, and U.S. Publication Nos. 2008/0187305;2012/0012748; 2011/0669189 and www.lytro.com/science_inside (allincorporated by reference).

Generally speaking, Plenoptic cameras combine a micro-lens array with asquare aperture and a traditional image sensor (CCD or CMOS) to capturean image from multiple angles simultaneously. The captured image, whichlooks like hundreds or thousands of versions of the exact same scene,from slightly different angles, is then processed to derive the rays oflight in the light field. The light field can then be used to regeneratean image with the desired focal point(s), or as a 3D point cloud. Thesoftware engine is complex, but many cameras include a GPU to handlesuch complicated digital processing.

Ideally, a plenoptic camera is about the same cost as a conventionalcamera, but smaller by eliminating the focus assembly. Focus can bedetermined by digital processing, but so can depth of field. If the mainimage is formed in front of the microlense array, the camera operates inthe Keplerian mode; with the image formed behind the microlense array,the camera is operating in the Galilean mode. See, T. Georgieu et al,Depth of Field in Plenoptic Cameras, Eurograhics, 2009.

With conventional photography, light rays 430 pass through opticalelements 432 and are captured by a sensor 434 as shown in FIG. 16A.Basically, a pixel 436 on the sensor 434 is illuminated by all of thelight rays 430 and records the sum of the intensity of those rays.Information on individual light rays is lost. With Light Fieldphotography (also referred to herein as “plenoptic”), information on allof the light rays (radiance) is captured and recorded as shown in FIG.16B. By capturing radiance, a picture is taken “computationally.” InFIG. 16B, an object 410 is imaged by a lense system 412. A virtual image414 appears at the computational plane 416, with the images combined onthe main sensor 420. The microlense array 418 has a plurality of sensorsthat each act as its own small camera that look at the virtual imagefrom a different position. In some plenoptic cameras, the array mightapproach 20,000 microlense and even have microlense with different focallengths giving a greater depth of field. With advances in silicontechnology, the arrays can grow quite large—currently 60 MP sensors areavailable—and Moore's law seems to apply, meaning quite large sensorarrays are achievable to capture richer information about a scene. Thecomputational power (e.g. GPU) to process these images is growing at thesame rate to enable rendering in real time.

With computational photography, the optical elements are applied to theindividual rays computationally and the scene rendered computationally.A plenoptic camera is used to capture the scene light ray information.Plenoptic cameras are available from Adobe, Lyto, Pelican Imaging ofPalo Alto, Calif. In such a plenoptic camera, microlenses are used tocreate an array of cameras to sample the plenoptic function. Typically,the picture would be rendered by using a GPU, such as from NVIDIA(GeForce 580), programmed using CUDA or Open GL Shader Language.

Expressed another way, a light field camera combines a micro-lens arraywith a software engine, typically running on a GPU to create a plenopticcamera. Essentially, the micro-lens array 418 is used with a squareaperture and a traditional image sensor 420 (CCD or CMOS) to capture aview of an object 410 from multiple angles simultaneously. The capturedimage, which looks like hundreds or thousands of versions of the exactsame scene, from slightly different angles, is then processed to derivethe rays of light in the light field. The light field can then be usedto regenerate an image with the desired focal point(s), or as a 3D pointcloud.

Therefore, in certain embodiments the use of a plenoptic camera andcomputational photography is believed preferable. To accuratelycalculate depth information in a scene with conventional cameras, twoimages must be compared and corresponding points matched. Depth is thenextracted by triangulation as explained herein. By using plenopticcameras and computational photography, some amount of stereo is builtinto the camera by using an array of microlenses. That is, the depth offield can be computed for different points in a scene.

IV. Network Operating Environment

By way of example, in FIG. 3 the communication network 205 of the system100 includes one or more networks such as a data network (not shown), awireless network (not shown), a telephony network (not shown), or anycombination thereof. It is contemplated that the data network may be anylocal area network (LAN), metropolitan area network (MAN), wide areanetwork (WAN), a public data network (e.g., the Internet), or any othersuitable packet-switched network, such as a commercially owned,proprietary packet-switched network, e.g., a proprietary cable orfiber-optic network. In addition, the wireless network may be, forexample, a cellular network and may employ various technologiesincluding enhanced data rates for global evolution (EDGE), generalpacket radio service (GPRS), global system for mobile communications(GSM), Internet protocol multimedia subsystem (IMS), universal mobiletelecommunications system (UMTS), etc., as well as any other suitablewireless medium, e.g., worldwide interoperability for microwave access(WiMAX), Long Term Evolution (LTE) networks, code division multipleaccess (CDMA), wideband code division multiple access (WCDMA), wirelessfidelity (WiFi), satellite, mobile ad-hoc network (MANET), and the like.

By way of example, the mobile devices smart phone 10, tablet 12, glasses220, and experience content platform 207 communicate with each other andother components of the communication network 205 using well known, newor still developing protocols. In this context, a protocol includes aset of rules defining how the network nodes within the communicationnetwork 205 interact with each other based on information sent over thecommunication links. The protocols are effective at different layers ofoperation within each node, from generating and receiving physicalsignals of various types, to selecting a link for transferring thosesignals, to the format of information indicated by those signals, toidentifying which software application executing on a computer systemsends or receives the information. The conceptually different layers ofprotocols for exchanging information over a network are described in theOpen Systems Interconnection (OSI) Reference Model.

In one embodiment, an application residing on the device 10 and anapplication on the content platform 207 may interact according to aclient-server model, so that the application of the device 10 requestsexperience and/or content data from the content platform 207 on demand.According to the client-server model, a client process sends a messageincluding a request to a server process, and the server process respondsby providing a service (e.g., providing map information). The serverprocess may also return a message with a response to the client process.Often the client process and server process execute on differentcomputer devices, called hosts, and communicate via a network using oneor more protocols for network communications. The term “server” isconventionally used to refer to the process that provides the service,or the host computer on which the process operates. Similarly, the term“client” is conventionally used to refer to the process that makes therequest, or the host computer on which the process operates. As usedherein, the terms “client” and “server” refer to the processes, ratherthan the host computers, unless otherwise clear from the context. Inaddition, the process performed by a server can be broken up to run asmultiple processes on multiple hosts (sometimes called tiers) forreasons that include reliability, scalability, and redundancy, amongothers.

In one embodiment, the crowdsourced random images and metadata can beused to update the images stored in a database. For example, in FIG. 3 anewly acquired image from a mobile device 10, 220 can be matched to thecorresponding image in a database 212. By comparing the time (metadata,e.g. FIG. 12) of the newly acquired image with the last update to thedatabase image, it can be determined whether the database image shouldbe updated. That is, as images of the real world change, the imagesstored in the database are changed. For example if the façade of arestaurant has changed, the newly acquired image of the restaurantfaçade will reflect the change and update the database accordingly. Inthe context of FIG. 3, the Image database 212 is changed to incorporatethe newly acquired image. Of course, the databases 212, 214 can besegregated as shown, or contained in a unitary file storage system orother storage methods known in the art.

In one embodiment, a location module determines the user's location by atriangulation system such as a GPS 250, assisted GPS (A-GPS) A-GPS, Cellof Origin, wireless local area network triangulation, or other locationextrapolation technologies. Standard GPS and A-GPS systems can usesatellites to pinpoint the location (e.g., longitude, latitude, andaltitude) of the device 10. A Cell of Origin system can be used todetermine the cellular tower that a cellular device 10 is synchronizedwith. This information provides a coarse location of the device 10because the cellular tower can have a unique cellular identifier(cell-ID) that can be geographically mapped. The location module mayalso utilize multiple technologies to detect the location of the device10. In a preferred embodiment GPS coordinates are processed using a cellnetwork in an assisted mode (See, e.g., U.S. Pat. Nos. 7,904,096;7,468,694; U.S. Publication No. 2009/0096667) to provide finer detail asto the location of the device 10. Alternatively, cloud based GPSlocation methods may prove advantageous in many embodiments byincreasing accuracy and reducing power consumption. See e.g., U.S.Publication Nos. 2012/0100895; 2012/0151055. The image Processing Server211 of FIG. 3 preferably uses the time of the image to post process theAGPS location using network differential techniques. As previouslynoted, the location module may be utilized to determine locationcoordinates for use by an application on device 10 and/or the contentplatform 207 or image processing server 211. And as discussed inconnection with FIG. 15, increased accuracy reduces the positioningerror of a target, reducing computational effort and time.

V. Data Acquisition, Conditioning and Use

The goal is to acquire as many useful images and data to build andupdate models of locations. The models include both 3D virtual modelsand images. A basic understanding of Photogrammetry is presumed by oneof ordinary skill in the art, but FIGS. 13a and 13b illustrate basicconcepts and may be compared with FIG. 16A. As shown in FIG. 13a , animage sensor is used, such as the CCD or CMOS array of the mobile phone10 of FIG. 3. Knowing the characteristics of the lens and focal lengthof the camera 140, 141 of the device 10 aids resolution. The device 10has a focal length of 3.85 mm and a fixed aperture of 2.97, and anFNumber of 2.8. FIG. 12 shows a common EXIF format for another cameraassociated with a Casio QV-4000. When a user of the camera 140, 141 inthe device 10 acquires an image, the location of the “point of origin”is indeterminate as shown in FIG. 13a , but along the vector or ray asshown. The orientation of the device 10 allows approximation of theorientation of the vector or ray. The orientation of the device 10 or220 is determined using, for example, the digital compass, gyroscope,and even accelerometer (FIG. 6). A number of location techniques areknown. See, e.g., U.S. Publication Nos. 2011/0137561; 2011/0141141; and2010/0208057. (Although the '057 publication is more concerned withdetermining the position and orientation —“pose”—of a camera based on animage, the reverse use of such techniques is useful herein where thecamera position and orientation are known.)

As shown in FIG. 13b , the unique 3D location of the target can bedetermined by taking another image from a different location and findingthe point of intersection of the two rays (i.e. stereo). A preferredembodiment of the present invention makes use of Photogrammetry whereusers take random images of multiple targets. That is, multiple userstake multiple images of a target from a number of locations. Knowingwhere a camera was located and its orientation when an image is capturedis an important step in determining the location of a target. Aligningtargets in multiple images allows for target identification as explainedherein. See, e.g., U.S. Pat. No. 7,499,079.

Image alignment and image stitching is well known by those of skill inthe art. Most techniques use either pixel to pixel similarities orfeature based matching. See, e.g., U.S. Pat. No. 7,499,079 and U.S.Publication No. 2011/0187746; 2012/478569; 2011/0173565. For example,Microsoft has developed algorithms to blend overlapping images, even inthe presence of parallax, lens distortion, scene motion and exposuredifferences in their “photosynch” environment. Additionally, Microsofthas developed and deployed its “Photosynth” engine which analyzesdigital photographs and generates a 3D model and a point mesh of aphotographed object. See, e.g., U.S. Publication Nos. 2010/0257252;2011/0286660; 2011/0312374; 2011/0119587; 2011/0310125; and2011/0310125. See also, U.S. Pat. Nos. 7,734,116; 8,046,691; 7,992,104;7,991,283 and U.S. Publication No. 2009/0021576.

The photosynth engine is used in a preferred embodiment of theinvention. Of course, other embodiments can use other methods known inthe art for image alignment and stitching. The first step in thePhotosynth process is to analyze images taken in the area of interest,such as the region near a point of interest. The analysis uses anfeature point detection and matching algorithm based on thescale-invariant feature transform (“SIFT”). See, the D. Lowe SIFT methoddescribed in U.S. Pat. No. 6,711,293. Using SIFT, feature points areextracted from a set of training images and stored. A key advantage ofsuch a method of feature point extraction transforms an image intofeature vectors invariant to image translation, scaling, and rotation,and partially invariant to illumination changes and local geometricdistortion. This feature matching can be used to stitch images togetherto form a panorama or multiple panoramas. Variations of SIFT are knownto one of ordinary skill in the art: rotation-invariant generalization(RIFT); G-RIFT (Generalized RIFT); Speeded Up Robust Features (“SURF”),PCA-SIFT, and GLOH.

This feature point detection and matching step using SIFT (or knownalternatives) is computationally intensive. In broad form, such featurepoint detection uses the photogrammetry techniques described herein. Inthe present invention, computation is diminished by providing veryaccurate positions and orientation of the cameras and using the metadataassociated with each image to build the 3D point cloud (e.g. model).

The step of using the 3D model begins with downloading the Photosynthviewer from Microsoft to a client computer. The basics of such a viewerderives from the DeepZoom technology originated by Seadragon (acquiredby Microsoft). See, U.S. Pat. Nos. 7,133,054 and 7,254,271 and U.S.Publication Nos. 2007/0104378; 2007/0047102; 2006/0267982; 2008/0050024;and 2007/0047101. Such viewer technology allows a user to view imagesfrom any location or orientation selected by a user, zoom in or out orpan an image.

VI. General Overview of Operation and Use

FIG. 1a shows a plaza 300 in a perspective view, while FIG. 1b is a planview of plaza 300. As an example, a plurality of images are taken bydifferent users in the plaza 300 at locations A-E at different times,FIG. 1 b. The data acquired includes the image data (including depthcamera data and audio if available) and the metadata associated witheach image. While FIG. 12 illustrates the common EXIF metadataassociated with an image, the present invention contemplates additionalmetadata associated with a device, such as available from multiplesensors, see e.g. FIGS. 5, 6, 10. In a preferred embodiment, as muchinformation as possible is collected in addition to the EXIF data,including the data from the sensors illustrated in FIG. 6. Preferably,the make and model of the camera in the device 10 is also known, fromwhich the focal length, lens and aperture are known. Additionally, in apreferred form the location information is not unassisted GPS, butassisted GPS acquired through the cell network which substantiallyincreases accuracy, both horizontal and vertical. By knowing the timethe image was taken and approximate location, differential correctionsand post processing can also be applied to the approximate location,giving a more precise location of the image. See, e.g., U.S. Pat. Nos.5,323,322; 7,711,480; and 7,982,667.

The data thus acquired from users at locations A-E using e.g. devices10, 12, or 220, are collected by the image processing server 211 asshown in FIG. 3. The data is preferably conditioned by eliminatingstatistical outliers. Using a feature recognition algorithm, a target isidentified and location determined using the photogrammetry techniquesdiscussed above. As can be appreciated, the more precise the locationswhere an image is acquired (and orientation) gives a more precisedetermination of target locations. Additionally, a converging algorithmsuch as least squares is applied to progressively determine more preciselocations of targets from multiple random images.

In the preferred embodiment, the camera model and ground truthregistration described in R. I. Harley and A. Zisserman, Multiple ViewGeometry in Computer Vision, Cambridge University Press, 2000 is used.The algorithm for rendering the 3D point cloud in OpenGL described in A.Mastin, J. Kepner, and J. Fisher, “Automatic Registration of LIDAR andOptimal Images of Urban Scenes,” IEEE 2009. See also, L. Liu, I. Stamos,G. Yu, G. Wolberg, and S. Zokai, “Multiview Geometry For Texture Mapping2d Images onto 3d Rang Data,” CVPR '06, Proceedings of the 2006 IEEEComputer Society Conference, pp. 2293-2300. In a preferred form, theLIDAR data of an image is registered with the optical image byevaluating the mutual information: e.g. mutual elevation informationbetween LIDAR elevation of luminance in the optical image; probabilityof detection values (pdet) in the LIDAR point cloud and luminance in theoptical image; and, the joint entropy among optical luminance, LIDARelevation and LIDAR pdet values. The net result is the creation of a 3Dmodel by texture mapping the registered optical images onto a mesh thatis inferred on the LIDAR point cloud. As discussed herein, in lieu of,or in addition to LIDAR, other depth cameras may be used in certainembodiments, such as plenoptic cameras, TOF cameras, or structured lightsensors to provide useful information.

For each point in the 3D mesh model, a precise location of the point isknown, and images acquired at or near a point are available. The numberof images available of course depends on the richness of the database,so for popular tourist locations, data availability is not a problem.Using image inference/feathering techniques (See U.S. Pat. No.7,499,079) images can be extrapolated for almost any point based on arich data set. For each point, preferably a panorama of images isstitched together and available for the point. Such a panoramaconstitutes a 3D representation or model of the environment from thechosen static point. Different techniques are known for producing mapsand 3D models, such as a point mesh model. See e.g. U.S. Pat. No.8,031,933; U.S. Publication Nos. 2008/0147730; and 2011/0199479.Further, the images may be acquired and stitched together to create a 3Dmodel for an area by traversing the area and scanning the area tocapture shapes and colors reflecting the scanned objects in the areavisual appearance. Such scanning systems are available from Matterportof Mountain View, Calif., which include both conventional images andstructured light data acquired in a 360′ area around the scanner. A 3Dmodel of an area can be created by scanning an area from a number ofpoints creating a series of panoramas. Each panorama is a 3D modelconsisting of images stitched to form a mosaic, along with the 3D depthinformation (from the depth camera) and associated metadata. In otherwords, traversing an area near a point of interest and scanning andcollecting images over multiple points creates a high fidelity 3D modelof the area near the point of interest.

Georeferenced 3D models are known, with the most common being DigitalSurface Models where the model represents the earth's terrain with atleast some of the surface objects on it (e.g. buildings, streets, etc.).Those in the art sometimes refer to Digital Elevation Models (DEM's),with subsets of Digital Surface Models and Digital Terrain Models. FIG.11 shows the earth's surface with objects displayed at various levels ofdetail, and illustrates a possible georeference of plaza 300 in an urbanenvironment. LIDAR is often used to capture the objects in georeferenceto the earth's surface. See, BLOM3D at http://www.blomasa.com.

FIG. 11a is a wire frame block model in an urban environment where the3D buildings are represented as parallelogram blocks, with noinformation on roofs or additional structures. This is the simplest datamodel.

FIG. 11b is a RoofTop Model that adds roof structure and otherconstructions present on the buildings. This is a much more detailed andprecise model and may include color.

FIG. 11c is a Library Texture Model adds library textures have been tothe Rooftop model of FIG. 11b . The result is a closer approximation ofreality, with a smaller volume of data than a photo-realistic model,which makes it ideal for on-board or navigation applications in whichthe volume of data is a limitation.

FIG. 11d is a Photo-realistic Texture Model that adds building texturesto the Rooftop model of FIG. 11b . The textures are extracted from theimagery, metadata and LIDAR information.

On top of any of the 3D models of FIG. 11 can be layered additionalinformation in even greater detail. The greater the detail (i.e. higherfidelity), the closer the model approximates photorealistic. That is,the 3D virtual model becomes realistic to an observer. The tradeoff, ofcourse, is having to handle and manipulate large data sets. Each modelhas its application in the context of the system and methods of thepresent invention. Any reference to a “3D model” when used in thepresent application should not imply any restrictions on the level ofdetail of the model.

FIG. 14 is a schematic to illustrate the process of image alignment andstitching, where mosaic 400 is the result of using images 402, 404, and406. Comparing FIG. 1b and FIG. 14, the assumption is that images 402,404, 406 correspond to images taken from locations A, B and Drespectively. The line of sight (i.e. the vector or ray orientation froma camera position) for each image 402, 404, 406 is used and described ina coordinate system, such as a Cartesian or Euler coordinate system. Theregion of overlap of the images defines a volume at their intersection,which depends on the accuracy of the locations and orientations of thecameras (i.e. pose) and the geometry of the images. However, the searchspace for feature recognition is within the volume, e.g. for applyingthe photosynth technique described herein. The contributions from eachimage 402, 404, 406 are used to form the mosaic 400. Such mosaicconstruction techniques are known, such as U.S. Pat. No. 7,499,079. Theboundaries are “feathered” to eliminate blurring and to provide a smoothtransition among pixels. Multiple mosaics can be constructed and alignedto form a panorama.

Once a 3D model has been created, there exists a variety of methods forsharing and experiencing the environment created. FIG. 17 illustratesone form of an experience viewing system, namely a room 500accommodating one or more users 510, which allows an experience to bewholly or partially projected within the room. See, U.S. Publication No.2012/0223885. In the embodiment shown in FIG. 17, a projection displaydevice 502 is configured to project images 504 in the room 500.Preferably the projection display device 502 includes one or moreprojectors, such as a wide-angle RGB projector, to project images 504 onthe walls of the room. In FIG. 17, the display device 502 projectssecondary information (images 504) and primary display 506, such as anLCD display, displays the primary information. However, it should beunderstood that either display 502 or 506 can operate without the otherdevice and display all images. Further, the positioning of the devices502, 506 can vary; e.g. the projection device 502 can be positionedadjoining primary display 506. While the example primary display 104 andprojection display device 502 shown in FIG. 17 include 2-D displaydevices, suitable 3-D displays may be used.

In other embodiments, users 102 may experience 3D environment createdusing glasses 220 (FIG. 10). In some forms the glasses 220 mightcomprise active shutter glasses configured to operate in synchronizationwith suitable alternate-frame image sequencing at primary display 506and projection display 502.

Optionally, the room 500 may be equipped with one or more camera systems508 which may include one or more depth camera and conventional cameras.In FIG. 17, depth camera 508 creates three-dimensional depth informationfor the room 500. As discussed above, in some embodiments, depth camera500 may be configured as a time-of-flight camera configured to determinespatial distance information by calculating the difference betweenlaunch and capture times for emitted and reflected light pulses.Alternatively, in some embodiments, depth camera 508 may include athree-dimensional scanner configured to collect reflected structuredlight, such as light patterns emitted by a MEMS laser or infrared lightpatterns projected by an LCD, LCOS, or DLP projector. It will beunderstood that, in some embodiments, the light pulses or structuredlight may be emitted by any suitable light source in camera system 508.It should be readily apparent that use of depth cameras, such as Kinectsystems, in camera system 508 allows for gestural input to the system.In addition, the use in camera system 508 of conventional cameras anddepth camera allows for the real time capture of activity in the room500, i.e. the creation of a 3D model of the activity of the users 510 inthe room 500.

FIG. 18 shows another room in the configuration of a wedding chapel 600.In the embodiment of FIG. 18, emphasis is on the capture of images andthe building of a 3D model of the events occurring within the weddingchapel 600. In the wedding chapel 600 the use of camera systems 602allows for the real-time capture of activity in the wedding chapel 600,i.e. the creation of a 3D model of the activity of the users in thewedding chapel 600. The camera systems 602 include a plurality of depthcameras and conventional cameras, and also microphones to capture theaudio associated with the wedding. Additional microphones (not shown)can be positioned based on acoustics of the room and the event to morefully capture the audio associated with the wedding.

In a preferred form, the wedding chapel 600 has been scanned in advanceof any event with a composite scanning system having both depth camerasand conventional cameras. Scans are taken at a large number of locationswithin the chapel 600 to increase the fidelity of the 3D model createdfor the chapel 600. The acquired scans are processed, i.e. by the imageprocessing server 211 of FIG. 3 and stored in a database for lateraccess by the experience platform 207.

During the event, i.e. the wedding, the camera systems 602 additionallycapture images (and audio) of the event. Further, one or more weddingguests are accompanied with a mobile device 10, 12, or 220, to captureimages and audio from the event and wirelessly convey the information tothe network 205 (FIG. 3). The information captured in real-time duringthe event are processed at server 211 (FIG. 3) and update the databases212, 214. The experience platform 207 is therefore accessible toobservers remote from the wedding chapel 600. It will be appreciatedthat such remote users can experience the event (wedding) by a varietyof methods, either historically or in real-time. As can be appreciatedfrom FIG. 3 the remote observers can use mobile devices 10, 12 or 220 toobserve the event. Additionally the remote observers can be present inroom 500 of FIG. 17 to observe the event.

VII. Examples of Use

A few examples are useful for illustrating the operation of the systemand methods hereof in a variety of contexts. It should be understoodthat the random images and associated metadata vary by time and spaceeven if taken in the same general area of interest. For example, theplaza 300 may be a point of interest, but the details of the 3D model ofthe plaza may be unknown or outdated. Further, while the methods andsystems hereof are useful outdoors where GPS is readily available,similar methods and systems can be applied indoors where locationdetermination is more challenging, but indoor positioning systems anddepth cameras can substitute for or augment GPS information. Further, inaddition to collecting data associated with a general region of a pointof interest, data can be segregated by time of acquisition, allowing forevent recreation and participation.

1. Crowdsourcing Images: Live News Event

A simple example is illustrated in FIG. 7. In FIG. 7, protesters 312,314 are imaged at the plaza 300 at a particular time (plaza 300 is alsoillustrated in FIGS. 1a and 1b ) by observers with mobile devices, 10,12, 220. Using multiple random images (random users and/or randomlocations and/or random orientations at random targets at random times)the protest demonstration (i.e. an event) can be captured and wirelesslysent to image processing server 211 via network 205 of FIG. 3. Theimages are processed to create or enhance a 3D model of the event (here,a protest) and stored in a database for access. The 3D model can be usedby a news organization as a replay over a period of time of thedemonstration. Further, a remote user can view the demonstration fromany location in or near the plaza 300 upon request to the contentexperience platform 207. In a simple case, still pictures and video canbe assembled over the time of the protest and accessed from theexperience platform 207.

For example, the observers recording the protest include depth camerainformation, the experience platform can also include a 3D model of theplaza 300 and protesters 312, 314. This allows a remote user to select aparticular viewing location in the plaza 300 from which to view theprotest. Where a large number of in-person observers have capturedimages, the 3D model can achieve a high degree of fidelity.

Consider a more complex example of an earthquake at sea resulting in atsunami wave that hits a major coastal city. As the wall of water wavecomes ashore its sets off a chain reaction of devastating floodingacross the entire city.

A cable news network issues an alert to its impacted viewers to uploadcaptured images from smart phone/devices 10, 12 or goggles 220 to adedicated, cloud-based server 211 using a downloaded camera phone app108, 112 (FIG. 4). Additionally high fidelity images from pre-positionedcameras, including depth cameras, throughout the city as well as aerialimages are also uploaded to the server 211.

Over 10,000 impacted citizens armed with camera equipped smart phones 10and goggles 220 from all over the city capture images (both photos andvideo with sound, depth information and associated metadata) of thedevastation and upload them to a cloud-based server 211 (either directlyor indirectly through image providers and social media). The scope ofuploaded content includes both exterior images and interior imageswithin city structures (e.g. buildings). The uploaded content can alsoinclude associated location and time specific social media content suchas Twitter postings.

The news organization uses the crowd-sourced content of the event todisplay in near real-time a panoramic/3D rendering of the tsunami'simpact along with a time lapsed rendering of the impact at a point ofinterest (e.g. a beach). The images, sounds and 3D model are availableto subscribers/users from the experience platform 207 by using theapplication 106. The application 106 allows many parts of the entire(image available) city to be observed and navigated from virtually anylocation and point of view that the individual user desires. Not onlycan the user navigate the 3D model of the city, but also the user canaccess panorama images from many user selected locations within themodel. Additionally, home users can access the 3D model usingintelligent TV, but also may use the mobile devices 10, 12, 220 as a“second screen” component to augment their television or monitor feed.

Additionally, the user can also view augmented reality enhancementsrelevant to the particular location they are viewing using a mobiledevice, such as mobile device 10, 12 or 220. For example: current waterdepth of flooding, high water level and the status of power availabilityto that area.

This crowd-sourced virtual rendering of the devastation is an essentialtool for both reporting the news but also managing the response effects.It also provides a living history that can be re-experienced (i.e.,Walked) at a later date using an enabled mobile network display devices,smart phone 10, 12 or goggles 220 for example.

Because the live rendering of the environment has real economic value toboth the news organization (audience size/advertising revenue) and theresponse organizations (efficient deployment of resources, protection oflife & property), those that contribute to the image bank are sometimescompensated for their sharing of their content. The experience metricsof those accessing the 3D environment of the city devastation (timespent, views, actions takes, sharing, related commerce, etc.) aretracked by the app and used for analytics to inform experienceoptimization and related commercial activity.

2. Rendered Environment For Applying Augmented Reality Enhancements:Retail Environment—Grocery Store

Every morning at the Acme Grocery Store, Bob the sales manager andmembers of his team walk the entire store while filming the availableproduct using their smart phones 10 and/or googles 220. There areadditional fixed cameras (such as camera systems 602, FIG. 18)throughout the store that capture and upload images every minute. Themobile devices either recognize the products directly using imagerecognition, or using QR codes or bar codes appearing near the availableproducts.

Bob and team upload the images to a processing server 211 thatprocesses/stitches the images into an updated 3D gestalt rendering ofthe store that can be viewed on any internet/GPS enabled device. In thisexample, uploading the images forces updates to popular 3rd partymapping services such as Google Maps or Bing maps, forcing the images tobe current. The images also update inventory and location of theproducts within the store.

As customers come onto the store (or remotely if they prefer) they canwalk the aisles and view freshly updated augmented reality messagesabout each product and associated promotional messages (pricing,specials, recipes, and/or nutritional info). The activity data(movement, time spent, AR interactions, purchases, etc.) of shoppers inthe store (both in-store and/or remote) is captured and uploaded to theserver for consolidation and analytics purposes.

Shoppers who experience the rendering of the store may not be dependenton using their phone's camera viewfinder. Rather, locations in the storeare determined using indoor positioning technologies (discussed herein)and updated with current images of the selections.

Rather than have to annoyingly point their phone's camera at theirtargets to view these augmented reality messages, multiple points ofview and “levels of detail” of the 3D store environment can be displayedand navigated on the customers smart phone 10 (or tablet 12 or glasses220) without depending on the phone's camera line of sight.

Users are not required to hold their camera phone 10 in front of theirface to enjoy the experience enhancements of augmented reality.

3. Mirror/Duplicate a Live Event Into Another Location: Super Bowl

This year's Super Bowl is being played in the Rose Bowl in Pasadena,Calif. before a sellout crowd of 75,000 fans. The Rose Bowl has beenmapped in advance, e.g. a Google Street View, where imagery, metadataand depth camera information is acquired and stored. That is, ahigh-fidelity 3D model of the Rose Bowl is created in advance,processed, and stored in databases 212, 214 for access via experienceplatform 207. The high fidelity images of the stadium, field and theparticipants have been uploaded to the image database 212.

The stadium had been retro-fitted with 5,000 wireless cameras (such ase.g. the camera systems 602 of FIG. 18) programmed to capture an imageevery 2 seconds and automatically upload these images to an imagerepository 216 and forwarded to a central processing server 211.

Similarly, every player's helmet is also fitted with a lightweight,wearable camera, combining a conventional camera with a depth camera andwith a microphone that also captures an image every second. Refereeshave similar cameras mounted on the hats. Each player and coach has alsobeen fitted with an image tag or marker to aid in augmented realitymessaging. Plenoptic cameras are advantageous in some respects becauseof their size (no lens), weight, and power requirements.

Finally, many fans attending the game are given or already possess awearable camera, e.g. goggles 220 (FIG. 10) that automatically capturesand uploads an image from their viewpoint periodically, e.g. every 5seconds. Any or all of the imaging and audio sensors on goggles 220 canbe used. The images are continuously wirelessly uploaded and processedby the network of FIG. 3.

The high speed processing of all these crowd-sourced images and audio isthen used to create a near live, virtual 3D model replicating the gamethat can be experienced in a number of new ways:

-   Projected as a mirror, live or near live 3D image and synthesized    audio into another stadium/venue for viewing by another group(s) of    spectators.    -   With augmented reality experience enhancements-   Projected as a miniaturized mirror, live or near live 3D image and    synthesized audio into a home viewing “table” or conference room    space.    -   With augmented reality experience enhancements-   On any network connected mobile device (smart phone 10, tablet 12,    goggles 220 or tv) a new 3D viewing experience is enabled that    allows a viewer to consume the experience from almost any    perspective of their choosing in the space (any seat, any players    point of view to any target or orientation, from above).    -   With augmented reality experience enhancements    -   Social media experience enhancements        -   “50 Yard Line Seats” is a concept whereby friends who live            in different locations could virtually all sit together at a            3D virtual live rendering of the game on their internet            enabled TV, computer, or tablet computer. This experience            would include the group video conferencing features now            found in Google+'s “Huddle” so that friends could interact            with each other as they all watched the game from the same            perspective. For example, the friends can access social            network 218 of FIG. 3 to interact with friends in a virtual            environment.

In one embodiment, the game viewing experience would be made moreimmersive by extending the crowd-sourced image and audio environment ofthe game beyond the television and onto the surrounding walls andsurfaces of a viewing room 500 as shown in FIG. 17. Using an the room500 creates an immersive environment approaching the sights and soundsof attending the game in person, creating the ultimate “man cave” for“attending” events. The server could also share metadata of the weathertemperature in the stadium with networked appliances (ie. HVAC) in theremote viewing structure to automatically align the temperature withthat of the event.

4. Living Maps: Appalachian Trial

Bob is planning a hiking trip of the Appalachian Trail, FIG. 8. Using anapplication that accesses crowd-sourced images and models from platform207 from hikers who have previous been on the trail, a 3D model of mostof the trail is available for Bob to view in advance on his networkenabled device. Further, pre-existing images and 3D models such aspanoramas are also available for many locations.

He can view the 3D rendered trail environment from a number of differentperspectives, locations and time periods (Fall, Winter, Spring, Summer).The rendering can also be enhanced with augmented reality type messagingabout the trail including tips and messages from previous trail hikers,sometimes called “graffiti.” In this example, Bob filters the imagesused to create the environment to be only from the last five years andlimits “graffiti” to members of his hiking club that are in his socialnetwork.

Bob uses the application to chart his desired course.

Bob will be hiking the trail alone but wants to have his father John to“virtually” join him on the journey. Bob uses a social media server toinvite his father and other friends to virtually join him. John acceptsBob invitation to join him which generates a notification to Bob and anevent in both their calendars.

On the day of the hike Bob has with him a GPS enabled smart phone 10 orgoggles 220. He launches the Appalachian Trail app, such as apps 108,110 of FIG. 4.

The launch of the apps 108, 110 sends an alert to John that Bob's hikehas started that John (and all the other friends that accepted Bob'sinvitation) can virtually join him.

John can access the application to join Bob's hike using his iPad 12, orgoggles 220 which sends an alert to Bob's phone 10.

On John's display he is able to view several photo-realistic 3Drendering options of the environment that Bob is in as he moves alongthe trail, e.g. FIG. 8. For example, John has the ability to followbehind Bob, view from above in plan view John as a dot on a map, run upahead on the trail or look behind. If fact all the activity data ofvirtual viewers is captured and uploaded to the server to provideanalytics for optimizing the design, usage and monetization of the 3Dtrail environment.

Bob is able to view the same 3D trail rendering on his smart phone 10 orgoggles 220 as his father John is viewing remotely. The virtualenvironment includes a number of “augmented reality” experienceenhancements including:

-   -   trail path    -   tip/messages from other hikers (both text and audio)    -   links to historical information    -   historical images of the trial    -   social media messages from those following his progress    -   time, speed and distance performance measurements    -   location and profile of others on the trial

Bob is able to view this information/rendering on his phone screen andis not required to use his phone's camera lens to access AR informationor trail renderings.

As Bob walks the trail he is able to have an on-going dialog with hisFather John and any of the other friends who have chosen to follow Bobusing a social media conferencing capability similar to Google+ Huddle.Remote viewers with properly equipped viewing rooms could make theirtrail viewing experience more immersive by extending the crowd-sourcedimage environment of the trail beyond the screen of an internet-enabledtelevision or device and onto the surrounding walls and surfaces of theviewing room using an environmental display.

As Bob enters areas of the trail that are not robust in their imagelibrary he get an alert on his phone from the App requesting that hecapture images on his phone 10 or goggles 220 and upload them to theprocessing server 211. Each image will contain information critical tocreating the 3D environment (time/date, GPS location, orientation,camera lens information, pixel setting, etc.).

These alerts help keep the trail images library robust and current onexperience platform 207.

5. Girls Night Out: Remote Sharing in a 4D Social Experience (4th isTime)

Jane is getting married next month but not before several of her bestgirl friends take her out for a proper bachelorette party at theirfavorite watering hole, The X Bar, as depicted in FIG. 9.

Jane has been posting about the upcoming party on her Facebook page andseveral of her out of town friends have asked to be able to remotelyshare in the experience.

Jane goes online and creates a Watch Me event on a social network andposts the link to her Facebook page.

She identifies The X Bar as the location of the event. Like a lot ofother popular venues, The X Bar has been retrofitted with audiomicrophones, conventional cameras, and wireless depth cameras, such asone or more camera systems 150 having a conventional camera, structuredlight camera (Kinect or Claris) and microphone to constantly captureaudio, images and movement activity throughout the inside of thefacility. Additionally, the X Bar has been scanned in advance and anexisting 3D model is stored in a database (e.g. FIG. 3). The camerasystems uploads images and audio in real-time to a cloud server such asserver 211. The X Bar makes these images, audio and movement activityavailable to applications like Watch Me to help create content thatdrives social buzz around their facility. That is, a remote user canaccess the images and 3D model in real-time via experience platform 207.Historical images inside the X Bar have been uploaded previously so theX Bar environment is known and available in fine detail from platform207. Real time images and audio from mobile devices 10, 220 accompanyingthe girl friends in attendance are also uploaded to server 211 andavailable for Jane's event. The X Bar is also equipped with projectioncapabilities, such as the projector 502 in FIG. 17, that allow a limitednumber of remote participants to be visibly present at select tables orregions of the room.

Several of Jane's girlfriends opt-in on social media to remotely sharein the bachelorette party experience. Betty, one of Jane's remotefriends, elects to be visibly present/projected at the event. Betty isin at a remote location that is optimized for immersive participation ofremote experience, such as the room 500 of FIG. 17. By extending thecrowd-sourced images and audio, the images and audio from camera systems150, layered on an existing 3D model creates an environment of the XBar. Use of the system of FIG. 17 by Betty extends the event experiencebeyond the screen of an internet-enabled television or mobile device andonto the surrounding walls and surfaces of the viewing room 500 usingone or more displays.

Conversely, Betty's image and movements are also captured by the camerasystem 508 of FIG. 17. Betty's image and movements (ex. Hologram) areprojected into X Bar using projector 502 of FIG. 9 into a pre-definedlocation (example wall or table seat) so her virtual presence can alsobe enjoyed by those physically at Jane's event.

Betty can also choose to have her projected presence augmented withvirtual goods (such as jewelry and fashion accessories) and effects(such as a tan, appearance of weight loss and teeth whitening).

On the night of the bachelorette party, Jane and each of the physicallypresent girls all use their camera equipped, smart phones 10 or goggles220 to log into the Watch Me application, such as app 108, 110.Throughout the night from 8 pm till 11 pm they use their smart phones 10or goggles 220 to capture images and audio of the party's festivitiesand wirelessly convey them to the network of FIG. 3.

The server 211 aggregates & combines all the images/video and audiocaptured that evening by all the linked image and audio sources; each ofthe girls smart phone or goggles cameras along with images provided byThe X Bar's real time image feed. This data is layered on top of thealready existing refined 3D model and images of the X Bar available onthe experience platform 207.

Each of these crowd-sourced images has detailed metadata (time, GPSlocation, camera angle, lens, pixel, etc.) that is used by theapplication to stitch together a 4D gestalt of the party experience.That can be enhanced with additional layers of augmented realitymessaging or imagery and/or audio. In addition, at least some of themobile devices include depth cameras permitting enhanced modeling of theevent.

The aggregation can be a series of photos that can be viewable from aparticular location or even a user's chosen location (e.g., Jane'sperspective) or preferably a 3D panorama form the user selectedlocation.

Sue is another one of Jane's friends that opted to view the eventremotely. Every 15 minutes she gets an alert generated by the Watch Meapp that another aggregation sequence is ready for viewing.

On her iPad 12, Sue opts to view the sequence from Jane's location andan exemplary orientation from the selected point of view. Sue can alsochoose to change the point of view to an “above view” (plan view) or aview from a selected location to Jane's location.

After viewing the sequence, Sue texts Jane a “wish I was there” message.She also uses the Watch Me application to send a round of drinks to thetable.

The day after the party Jane uses the Watch Me app to post a link to theentire 4D photorealistic environment of the entire bachelorette partyevening to her Facebook page for sharing with her entire network.Members of the network can view the event (and hear the audio) from aselected location within the X Bar.

6. Mobile Social Gaming

Bob and three of his friends are visiting Washington D.C. and areinterested in playing a new city-specific mobile “social” multiplayergame called “DC—Spy City.” The game is played using internet enabledmobile phones 10, tablets 2 or googles 220 and the objective is to findand capture other players and treasure (both physical and virtual) overthe actual landscape of the city.

Using crowd-sourced images of Washington D.C. and the real time GPSlocation of each player, a real-time 3D photo-realistic game environmentis rendered for each player. Game players and local and remote gameobservers can individually select from various points of view forobserving (above, directly behind, etc) any of the game participantsusing an internet connected device.

These environments can also be augmented with additional messaging tofacilitate game play information and interaction.

7. Virtual Trade Show

Bill wants to attend CES the electronics industry's major trade show buthis company's budget can't afford it. The CES event organizers estimatethat an additional 2,000 people are like Bill and would be interested inattending the event virtually.

To facilitate that, fixed cameras have been strategically placed throughthe event hall and in each of the exhibitor booths and presentationrooms. Images and audio are captured using camera systems, such assystems 602 of FIG. 18, and used to create a live, 3D, photo-realisticenvironment from which remote attendees can virtually walk andparticipate in the trade show.

The event has also created a companion augmented reality applicationthat helps integrate these virtual attendees into the trade show,allowing them to engage with actual event participants, presenters,objects in the booth and exhibitors. Additionally, each exhibitor hasequipped their booth representatives with internet-based videoconferencing mobile devices (ie. Goggles 220) so that they can directlyinteract and share files & documents with the virtual attendees thatnavigate to their booth. Remote participant activity data (pathtraveled, booths visited, time spent, files downloaded, orders place)within the virtual trade show from the virtual trade show environment iscaptured and shared with the server.

Bill can interact with the event remotely by positioning himself in aroom, such as room 500 of FIG. 17. However, Bill elects to participatewith his desktop computer by accessing the experience platform 207 ofFIG. 3. From his desktop, Bill can virtually walk through the 3D modelof the convention hall and interact with people and objects usingartificial reality.

8. Wedding Venue

Distance and the cost of travel are often barriers to friends and familyattending a wedding. To address that issue the Wedding Chapel 600 ofFIG. 18 has installed a number of fixed camera systems 602 that includedepth cameras, such as Kinect, along with high fidelity sound imagesfrom light field cameras (plenoptic) throughout the venue so that itsoptimized for live/near remote, three-dimensional viewing and experiencecapture.

Will and Kate are being married overseas in London and many of theirclose friends cannot attend the wedding but want to actively participatein the experience remotely.

Prior to the event, each of the remote viewers registers theirattendance at the Wedding Chapel website and downloads an application totheir internet enabled display device to manage their consumption andparticipation of the wedding event. The application is also integratedwith invitation/rsvp attendee information so a complete record of bothphysical and virtual attendees is available along with their profileinformation (ex. relation to couple, gift, well wishes).

Will has asked his brother Harry to be his best man. Because Harry iscurrently stationed overseas on active military duty he will serve asBest Man remotely and projected into the experience.

During the ceremony Will is at a remote location that is optimized forimmersive participation in remote experience by extending thecrowd-sourced image, audio and movement environment of the WeddingChapel beyond the screen of an internet-enabled television or displaydevice and onto the surrounding walls and surfaces of the viewing roomusing an environmental display, such as the room 500 of FIG. 17. Thatis, during the ceremony Will can view the event via projectors 502, 506while camera system 508 captures Will's movements, images, and audio fortransmission to the network system 100.

That is, Will's image and movements are captured and projected (ex.Hologram) into a pre-defined location (ex. near the altar) within theWedding Chapel 600 of FIG. 18 so his virtual presence can also be viewedby those physically (as well as remotely) at the wedding.

On the day of the wedding, the application notifies the remote attendeeswhen the event is ready for viewing. Each remote viewer has the abilityto watch the wedding from any number of perspective views/locations fromwithin and outside of the wedding chapel. These views can be stationary(third row/2nd seat or over the ministers shoulder) or moving(perspective from behind the bride as she walks down the aisle) or evenfrom the bride or groom's location.

After the ceremony the happy couple has access to a 4D gestalt (4=time)of their wedding experience that they can “re-experience” from anynumber of perspectives from within and outside the Wedding Chapelwhenever they like, even sharing with members of their social network.

What is claimed:
 1. A system for creating and sharing an environmentcomprising: a network for receiving images and metadata from a pluralityof devices each having a camera employed near a point of interest tocapture images and associated metadata near said point of interest,wherein the metadata for each image includes location of the device andthe orientation of the camera, at least some of said devices including adepth camera capturing range between the depth camera and targets nearsaid point of interest, the metadata for each image includes range toone or more targets; an image processing server connected to the networkfor receiving said images and metadata, wherein the server processes theimages and metadata to build a 3D model of one or more targets proximatethe point of interest based at least in part on said images andmetadata, said 3D model comprising the location of a number of saidtargets near said point of interest where target location is based atleast in part on device location and range; an experience platformconnected to the image processing server for storing the 3D model of oneor more targets, operable whereby users can connect to the experienceplatform to view the one or more targets near the point of interest froma user selected location and orientation and view the 3D model of one ormore targets.
 2. The system of claim 1 wherein the network includeswireless access and some of the devices are mobile, wherein the imagesare crowdsourced at random from users of the mobile devices.
 3. Thesystem of claim 1, wherein the experience platform includes a pluralityof images associated with locations near the point of interest and auser connected to the experience platform can view images associatedwith a user selected location and orientation.
 4. The system of claim 1,wherein the processing server is operable to stitch a number of imagestogether to form a panorama.
 5. The system of claim 4, wherein a userconnected to the experience platform can view panoramas associated witha user selected location and orientation.
 6. The system of claim 1,wherein said images include advertising based on context.
 7. A methodfor creating an environment for use with a location based experience,comprising: collecting images and associated metadata captured near apoint of interest with a plurality of mobile devices accompanying anumber of crowdsource contributors, one or more mobile device having aconventional RGB camera and a depth camera operable to capture images,wherein the associated metadata for each image includes location of themobile device, an orientation of the camera and range between the depthcamera and a target near said point of interest; receiving said imagesand metadata from said mobile devices at an image processing server; andprocessing the images on said image processing server to determine thelocation of one or more targets in the images and to build a 3D model ofone or more targets near the point of interest, said 3D model comprisingthe location of a number of said targets near said point of interestwhere target location is based at least in part on device location andrange.
 8. The method of claim 7, at least some of said mobile devicescomprising a depth camera having two or more conventional cameras in astereo triangulation.
 9. The method of claim 7, the depth camera is atime of flight camera, a structured light sensor, a stereo triangulationor a plenoptic camera.
 10. The method of claim 7, wherein saidprocessing step includes using an existing 3D model of a target andenhancing said existing 3D model using said randomly captured images andmetadata.
 11. The method of claim 7, wherein said randomly capturedimages are crowdsourced from a plurality of contributors withoutcoordination among said users.
 12. A method of sharing content in alocation based experience, comprising: capturing a plurality of imagesand associated metadata near a point of interest using one or moreconventional cameras and one or more depth cameras; processing thecaptured images and associated metadata to build a 3D model of one ormore targets near said point of interest, said 3D model comprising thelocation of a number of said targets near said point of interest wheretarget location is based at least in part on a camera location and rangefrom said camera to a target; storing the images, metadata, and the 3Dmodel in an experience platform connected to a network; accessing theexperience platform using the network to access the 3D model and images;selecting a location and orientation near said point of interest; andviewing the 3D model of one or more targets using the selected locationand orientation.
 13. The method of claim 12, including viewing the 3Dtarget model and an advertisement based on context.
 14. The method ofclaim 12, including removing 3rd parties from the images stored in theexperience platform prior to viewing and including members of a socialnetwork in the images stored in the experience platform.
 15. The methodof claim 12, wherein said captured images are randomly captured bycrowdsource from users equipped with mobile devices without coordinationof targets or time of acquisition among users.
 16. The method of claim15, wherein each mobile device includes at least one depth cameracapturing depth information comprising range between the depth cameraand a target near said point of interest.
 17. The method of claim 12,wherein the depth camera is a time of flight camera, a structured lightsensor, a stereo triangulation or a plenoptic camera.
 18. The method ofclaim 12, wherein said processing step includes receiving an existing 3Dmodel of a target and enhancing said preexisting 3D model using saidcaptured images and metadata.
 19. The method of claim 12, wherein saidviewing step includes wearing goggles and viewing a point of interestwith at least some of the target enhanced with artificial reality. 20.The method of claim 12, wherein said viewing step includes a user remotefrom said selected location.
 21. The method of claim 20, wherein saidremote user views said target model on a mobile device.
 22. The methodof claim 21, wherein said remote user views said target model projectedinto the remote user's environment.
 23. The method of claim 15,including analyzing said random images and metadata to determine users'interests based at least in part on images acquired and/or time ofacquisition.
 24. The method of claim 12, wherein some of the images arerandomly captured by crowdsource from users equipped with mobile deviceswith the images captured about the same time to build a 3D model of oneor more targets representative of an approximate time.
 25. The system ofclaim 1, wherein some of the devices including a depth camera are infixed locations proximate said point of interest and operable to trackpeople and objects.
 26. The system of claim 1, wherein some of thedevices including a depth camera accompany mobile users proximate saidpoint of interest and operable to track said mobile user.
 27. The systemof claim 1, wherein some of the devices including a depth camera thataccompanies mobile users and the depth camera is incorporated intoglasses worn by the mobile user.